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» Genetic Algorithms for the Design of Fuzzy Neural Networks
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GECCO
2007
Springer
148views Optimization» more  GECCO 2007»
14 years 1 months ago
Fuzzy-UCS: preliminary results
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. Fuzzy-UCS combines the generalization capabilities of UCS...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
AIIA
2001
Springer
14 years 2 days ago
A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data
– This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning al...
Giovanna Castellano, Anna Maria Fanelli
IJCNN
2000
IEEE
13 years 12 months ago
Supervised Scaled Regression Clustering: An Alternative to Neural Networks
: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...
GECCO
2005
Springer
160views Optimization» more  GECCO 2005»
14 years 1 months ago
Designing resilient networks using a hybrid genetic algorithm approach
As high-speed networks have proliferated across the globe, their topologies have become sparser due to the increased capacity of communication media and cost considerations. Relia...
Abdullah Konak, Alice E. Smith
EOR
2007
151views more  EOR 2007»
13 years 7 months ago
A possibilistic decision model for new product supply chain design
This paper models supply chain (SC) uncertainties by fuzzy sets and develops a possibilistic SC configuration model for new products with unreliable or unavailable SC statistical...
Juite Wang, Yun-Feng Shu